Data Engineer

Steer Bridge is a modern technology company delivering innovative, mission‑focused solutions to the U.S. Government and private sector.Leveraging deep expertise in federal acquisition, digital transformation, and emerging technologies, we deliver agile, commercial‑grade capabilities that accelerate operational effectiveness and drive measurable mission success.

At the core of Steer Bridge is our people—especially the veterans whose leadership, problem‑solving mindset, and commitment to excellence elevate every project we support. We don’t simply hire exceptional talent;
we cultivate it
, creating meaningful career pathways for veterans, military spouses, and professionals who share our passion for advancing technology and strengthening the missions we serve.

Steer Bridge is seeking a Data Engineer (Mid-Level, 3+ years) to join our growing Aviation team at our headquarters in Tysons Corner (Vienna, VA). In this role, you will support a major federal transformation effort by modernizing and optimizing complex data systems at scale, working alongside architects, analysts, and data scientists to design efficient data flows, enhance data quality, and ensure secure, reliable pipelines for both real-time and batch processing environments.

Our projects span AI/ML, cloud architecture, and large-scale data engineering to help modernize critical federal systems. This is a full‑time, on‑site position based in Vienna, VA (3-5 days/week on‑site; hybrid arrangements available at supervisors' discretion).

• Build, optimize, and maintain batch and real‑time data ingestion pipelines, including ETL/ELT processes for structured and unstructured data.
• Lead design and implementation of scalable ETL processes across complex, distributed systems, and develop and manage data lake architecture for structured and unstructured data.
• Use tools such as dbt, Informatica, Azure Data Factory, Databricks, and AWS Glue for data transformation and workflow automation, and utilize AWS services (Event Bridge, S3 Event Notifications) for workflow orchestration and scheduling.
• Write performant SQL queries and Python/JavaScript scripts for data parsing, ingestion, and cleanup.
• Conduct data profiling, linkage, validation, and quality checks across diverse sources; ensure data quality, lineage, governance, and compliance across all systems.
• Enable cloud-based data processing (e.g., AWS S3, Azure Blob) and support API integration.
• Collaborate across data science, engineering, and stakeholder teams to deliver accurate and actionable data products, and support reporting and model development with the software team and data scientists.
• Mentor junior engineers, providing technical guidance and peer reviews.
• Maintain technical documentation for pipelines, data structures, infrastructure, standards, and data product specifications.
• Support secure data governance practices and performance tuning in modern cloud platforms.

• Must be a U.S. Citizen.
• Bachelor's degree in Computer Science or a related field, with a minimum of three (3) years of relevant work experience.
• An active security clearance, or the ability to obtain one, is required.
• Strong proficiency in Python and SQL.
• Hands‑on experience with Pandas, PySpark, and AWS Glue.
• Deep understanding of ETL frameworks, data lake design, and cloud-based architecture.
• Familiarity with real‑time and batch data processing tools and methodologies.
• Experience with data governance, security compliance, and maintaining data quality standards; responsible for safeguarding sensitive information and adhering to organizational security and privacy policies.
• Must be local to the Vienna, VA area and able to work on‑site at our Vienna, VA office (3-5 days/week); hybrid arrangements available at supervisors' discretion.

• Experience with dbt, Informatica, Azure Data Factory, and Databricks for data transformation and workflow automation.
• Experience with AWS orchestration services such as Event Bridge and S3 Event Notifications.
• Experience mentoring junior engineers and leading design of scalable ETL processes across complex, distributed systems.
• Famili…